Acoustic Emission Analysis Research Articles

A Study on Damage of T800 Carbon Fiber/Epoxy Composites under In-Plane Shear Using Acoustic Emission and Digital Image Correlation.

In addition to measuring the strain, stress, and Young's modulus of materials through tension and compression, in-plane shear modulus measurement is also an important part of parameter testing of composites. Tensile testing of ±45° composite laminates is an economical and effective method for measuring in-plane shear strength. In this paper, the in-plane shear modulus of T800 carbon fiber/epoxy composites were measured through tensile tests of ±45° composite laminates, and acoustic emission (AE) was used to characterize the damage of laminates under in-plane shear loading. Factor analysis (FA) on acoustic emission parameters was performed and the reconstructed factor scores were clustered to obtain three damage patterns. Finally, the development and evolution of the three damage patterns were characterized based on the cumulative hits of acoustic emission. The maximum bearing capacity of the laminated plate is about 17.54 kN, and the average in-plane shear modulus is 5.42 GPa. The damage modes of laminates under in-plane shear behavior were divided into three types: matrix cracking, delamination and fiber/matrix interface debonding, and fiber fracture. The characteristic parameter analysis of AE showed that the damage energy under in-plane shear is relatively low, mostly below 2000 mV × ms, and the frequency is dispersed between 150-350 kHz.

Characterizing fatigue damage evolution in asphalt mixtures using acoustic emission and Gaussian mixture model analysis

The identification and investigation of fatigue crack evolution and damage modes in asphalt mixtures are crucial for understanding the corresponding mechanisms and characteristics of fatigue failure. In this study, the four-point bending fatigue tests were performed on the asphalt mixture specimens with precast joints using the acoustic emission (AE) technique to analyze the damage evolution. The failure modes of the asphalt mixtures were identified using the Gaussian mixture model (GMM). The results revealed that the fatigue damage of the asphalt mixtures can be categorized into four stages: Stage I (void compaction), Stage II (microcrack initiation and stable propagation), Stage III (crack aggregation and unstable propagation), and Stage IV (complete fracture). This division was defined based on the inflection points of the axial displacement curves, the cumulative number of AE events, and the cumulative ringing counts. The evolution of the AE b value was found to be correlated with the crack propagation. The rapid decline in the b value in Stage III was considered a harbinger of the eventual complete fracture in the asphalt mixtures. The GMM clustering analysis indicated that the fatigue damage of the asphalt mixtures primarily involved tensile damage (90%), and shear damage made a small contribution of 10%. Existing AE studies have focused on the quantitative evaluation of AE parameters, while research on clustering identification algorithms for these parameters is scarce. The analytical methods and findings of this study enable an effective identification of fatigue damage in asphalt mixtures at the laboratory scale and offer insights into the fatigue damage mechanisms of asphalt mixtures.

Acoustic Stall Detection of Variable Pitch Propeller for Unmanned Aerial Vehicles

This paper presents an analysis of acoustic emission and performance data of a UAV rotor equipped with a variable pitch propeller. The proposed study aims to show propeller noise features that indicate stall flow regime on the blade. Analysis of the noise characteristics around the propeller in terms of power spectral density allow to detect the stall. The study shows that a microphone located at different angles around the propeller can provide data sufficient to determine if the blade angle of attack has forced the propeller into the stall regime. In this range, the propeller’s efficiency in hover decreases and leads to an increase in power consumption. The reresearch is a suggests a method of data treatment to obtain a single parameter indicating a blade stall.

Research and prediction of creep behavior of triaxial warp‐knitted composites by time–temperature equivalent principle

AbstractIn this paper, the creep behavior of triaxial warp‐knitted composites (TWKC) was investigated. The TWKC specimens were prepared by applying vacuum‐assisted resin infusion (VARI), and the three‐point bending creep experiments at different temperatures were carried out. The shift factor was calculated based on the activation energy method, and the creep curve at 25°C within 105s was obtained according to the time–temperature equivalence principle, the time–temperature equivalent model was established, and the model was verified by measuring the long‐term creep data with self‐made instrument. There is approximately agreement between the prediction result and experimental one, which is less than 10% within 105s. The results show that the model could be used to predict the creep behavior of TWKC. The viscoelastic properties of the specimen were analyzed based on dynamic mechanical analysis (DMA), and the creep behavior of TWKC was further analyzed by acoustic emission and digital image correlation damage analysis.Highlights The viscoelasticity of TWKC was analyzed based on dynamic mechanical analysis (DMA), and the activation energy was calculated. Based on the activation energy method, the time–temperature equivalent model was established to predict the creep behavior of TWKC. The creep behavior of TWKC were further analyzed by acoustic emission (AE) and digital image correlation (DIC) damage analysis.

Enhancing cementitious grouting performance through carbon nanotube-coated fly ash incorporation

Cementitious composites reinforced with carbon nanotubes (CNTs) offer notable benefits compared to conventional cement-based materials in terms of durability and strength. Despite these advantages, the widespread implementation of CNTs in cement-based grouting engineering has not been carried out due to the limitations of dispersion issues. In order to facilitate the progression of carbon nanotubes (CNTs) from laboratory experiments to engineering applications, we proposed a method of using amino-functionalised functional groups to coat CNTs on the fly ash (FA) particles’ surfaces to assist the dispersion and prepare cost-effective, low-carbon emission, energy consumption-saving and high-performance cementitious slurry. The experimental results exhibit that compared with plain cement-based grouting materials, incorporating 0.023 wt% CNTs and 14.3 wt% FA can reinforce the compressive and tensile strength by 14.2–25.8% and improve the workability by about 21.0%. The application of coated CNTs induces nucleation and pore-infilling effects within the interfacial transition zone (ITZ) of the cementitious composites. This action leads to a reduction in ITZ width and a decrease in crack occurrence within the ITZ. Consequently, these effects contribute to an augmentation in the consolidation strength of the slurry. Acoustic emission and fracture surface fractal analysis further reveal that incorporating CNTs enhances the resist-loading ability of the cement matrix by increasing its energy absorption capability. The innovative coating method reported in this work is expected to facilitate the future application of CNTs in practical grouting engineering.

Fracture behaviour of plasma electrolytic oxide coatings on an aluminium substrate using acoustic emission

Due to their low density and high specific strength, aluminium alloys provide a great range of application, but they are limited regarding corrosion and wear resistance. Plasma electrolytic oxidation (PEO) is an innovative process to produce oxide ceramic surfaces on aluminium to protect against corrosion and wear. However, due to their brittle nature and an unfavourable residual stress ratio (substrate/coating), PEO coatings have a limited fatigue resistance. The characterisation of the failure behaviour using conventional material testing methods is mostly elaborate and time-consuming. Furthermore, microstructure analysis methods using metallographically prepared specimen sections only provide local two-dimensional information about failure. In contrast, acoustic emission (AE) analysis is an integral method for the examination of the cracking behaviour and fracture mechanisms of materials. However, its application for PEO coatings is a novel approach. In this work, the suitability of the AE analysis for these coatings is evaluated by the characterisation of the fracture and failure behaviour under three-point bending loading. Since the fatigue test is a complex loading case, the focus is first on the static test. Signals were acquired during mechanical testing using an AE sensor and processed by Fourier transform. Two characteristic frequency bands between 150 kHz and 250 kHz as well as 350 kHz and 450 kHz were observed in the generated frequency spectra. From the correlation with the microscopic images, the low-frequency band was assigned to vertical surface cracks, whereas the higher-frequency band was primarily attributed to horizontal interface cracks.

Acoustic sensing for investigating critical heat flux enhancement during pool boiling on electrodeposited copper foams

Nano-engineered surfaces have shown great promise in improving boiling heat flux and heat transfer coefficient for thermal management. Electrodeposited copper foams have attracted lots of scientific and engineering interest owing to their multi-tier structures. In this study, hierarchical copper foams with ultra-wicking properties were fabricated using cathodic deposition at different pH, including both acidic (pH 0) and basic (pH 10 and 12) solutions. Pendant droplet wicking tests and pool boiling experiments were performed to characterize the wicking flux and the critical heat flux (CHF) of the fabricated copper foams, respectively. The CHF enhancement mechanism in hierarchical copper foams was investigated with high-speed optical imaging and acoustic emission (AE) sensing during both the wicking and boiling tests. The results show that the wicking flux of the electrodeposited copper foams increases with the pH due to smaller dendrites and crystallites. Boiling CHF is also higher on the base-deposited copper foams (pH 10 and pH 12) than on the acid-deposited foams (pH 0). Consistent acoustic signatures are observed between wicking and boiling, i.e., smaller AE amplitudes are observed at higher wicking flux and higher CHF, which supports wicking-based CHF enhancement theories. A spike in the AE amplitude is observed at CHF during water boiling on copper foam surfaces due to the rapid growth of the vapor layer blanketing the boiling surface. During the nucleate boiling regime, the AE amplitude decreases with the heat flux in the low heat flux stage but increases with the heat flux in the high heat flux stage. This relationship is found to be due to the interplay of bubble size and bubble count in the stress field that bubbles exert on the heater surface. By analyzing the maximum bubble size, bubble count, and the power and dominant frequency of vapor fraction at varying heat fluxes from high-speed videos, our work shows no obvious effect of the surface structures on the dynamics of the apparent liquid–vapor interface. Combining the optical and acoustic analysis, it is concluded that the key role that surface structures play in CHF enhancement is improving capillary wicking underneath the bubbles rather than affecting the dynamics of the apparent liquid–vapor interfaces. This study not only explores the relationship between electrochemical control and wicking properties but also demonstrates the role of wicking in structure-enhanced boiling CHF through acoustic emission analysis.

Tracing fracture damage evolution and identifying damage patterns in cast steel using advanced acoustic emission analysis

The application of advanced acoustic emission signal analysis techniques can facilitate the identification of fracture damage modes in ductile materials and enable the provision of fracture precursor warnings. Given the vast array of acoustic emission signal characteristic parameters, there must be a systematic and comprehensive basis for selection and a deep comparison among different fracture warning indicators. This study uses G20Mn5QT cast steel material fracture acoustic emission monitoring tests under different in-plane constraints as an example. We adopted principal component analysis and k-means++ to select acoustic emission feature parameters and cluster damage modes. Additionally, we conducted a comparative analysis of several fracture precursor warning indicators and influencing factors, including fractal dimensions, b/Ib values, and natural time analysis. Our findings show that shear and tensile fracture damage modes are present in type-I fracture tests when applying the k-means++ cluster to the rise angle-average frequency-energy parameter, but tensile fracture modes dominate. Fractal dimensions, b-values, and Ib-values show a strong trend correlation with the fracture damage evolution process. Natural time analysis can quantitatively provide the moment of fracture precursor warnings, but the sliding window length inversely affects the absolute value sizes. Through acoustic emission signal analysis, our research provides a reference for identifying and examining the evolution of fracture damage in ductile materials and engineering components.

Interface failure identification of argon/nitrogen double plasma modified hybrid laminated para‐aramid composites

AbstractThis work reveals the synergistic effect of argon/nitrogen double plasma alteration on the mechanical properties of para‐aramid fiber/epoxy resin composites with various laminating sequences. Acoustic emission monitored interface failure during tensile, bending and fracture testing. A comparative analysis was conducted on the bending performance of the composites modified by argon/nitrogen double plasma and single plasma. The results showed that the synergistic effect of nitrogen and high‐energy molecule argon optimized the modifying effect of argon/nitrogen double plasma. The optimal modification parameters obtained through fiber extraction testing analysis are power 200 W, time 120 s, and Ar/N2 double gas flow rate of 12 sccm. After plasma treatment, twill weave modifies better than plain weave. The AE signal amplitude of PX1 is minimized during stretching. Due to the difference in internal bending stiffness of PX2, interface delamination failure is more likely to occur. The PX5 had greater fiber and matrix debonding failure between mode‐II fracture tests due to the weak modification effect of plain weave and its difficulty in deformation. In ballistic testing, PX1 blocks impact force through fiber bundle stretching deformation, while PX4 is more brittle.Highlights Prepare para‐aramid/epoxy resin composites with various laminating sequences. Study on the interfacial properties of composites treated with double plasma. The composites with different gas sources treatment were analyzed. Acoustic emission analysis was used to identify interface failure modes. The bonding strength between plain and plain interfaces is the lowest.

Laboratory study on the effect of stress cycling pattern and rate on seismicity evolution

Recent laboratory and field studies suggest that temporal variations in injection patterns (e.g., cyclic injection) might trigger less seismicity than constant monotonic injection. This study presents results from uniaxial compressive experiments performed on Red Felser sandstone samples providing new information on the effect of stress pattern and rate on seismicity evolution. Red Felser sandstone samples were subjected to three stress patterns: cyclic recursive, cyclic progressive (CP), and monotonic stress. Three different stress rates (displacement controlled) were also applied: low, medium, and high rates of 10−4 mm/s, 5 × 10−4 mm/s, and 5 × 10−3 mm/s, respectively. Acoustic emission (AE) waveforms were recorded throughout the experiments using 11 AE transducers placed around the sample. Microseismicity analysis shows that (i) Cyclic stress patterns and especially cyclic progressive ones are characterized by a high number of AE events and lower maximum AE amplitude, (ii) among the three different stress patterns, the largest b-value (slope of the log frequency-magnitude distribution) resulted from the cyclic progressive (CP) stress pattern, (iii) by reducing the stress rate, the maximum AE energy and final mechanical strength both decrease significantly. In addition, stress rate remarkably affects the detailed AE signature of the events classified by the distribution of events in the average frequency (AF)—rise angle (RA) space. High stress rates increase the number of events with low AF and high RA signatures. Considering all elements of the AE analysis, it can be concluded that applying cyclic stress patterns in combination with low-stress rates may potentially lead to a more favourable induced seismicity effect in subsurface-related injection operations.

Effects of Water Saturation and Loading Condition on Rock Tensile Strength: Insights from Acoustic Emission Analysis

Effects of Water Saturation and Loading Condition on Rock Tensile Strength: Insights from Acoustic Emission Analysis

Monitoring of Joint Gap Formation in Laser Beam Butt Welding using Neural Network-Based Acoustic Emission Analysis

This study aimed to explore the feasibility of using airborne acoustic emission in laser beam butt welding for the development of an automated classification system based on neural networks. The focus was on monitoring the formation of joint gaps during the welding process. To simulate various sizes of butt joint gaps, controlled welding experiments were conducted, and the emitted acoustic signals were captured using audible-to-ultrasonic microphones. To implement an automated monitoring system, a method based on short-time Fourier transformation was developed to extract audio features, and a convolutional neural network architecture with data augmentation was utilized. The results demonstrated that this non-destructive and non-invasive approach was highly effective in detecting joint gap formations, achieving an accuracy of 98%. Furthermore, the system exhibited promising potential for the low-latency monitoring of the welding process. The classification accuracy for various gap sizes reached up to 90%, providing valuable insights for characterizing and categorizing joint gaps accurately. Additionally, increasing the quantity of training data with quality annotations could potentially improve the classifier model’s performance further. This suggests that there is room for future enhancements in the study.

Acoustic Emission Sensor-Assisted Process Monitoring of Air Plasma-Sprayed Titanium Deposition

AbstractAcoustic emission is a sensing technique that offers the potential benefit for its use as an in situ monitoring tool for a wide range of manufacturing processes. This work attempts to highlight the robustness of using acoustic emission (AE) data for in-line process monitoring of the air plasma spray deposition technique. As part of this study, titanium powder was deposited under various conditions of robot speed, powder feed rates and the influence of these changes were investigated in the signature obtained from the AE analysis. The post-processed AE data showed sensitivity to these changes through variation in frequencies, power spectral densities and the cumulative energy that gets transmitted to the substrate during the spraying process. The AE signal sensitivity was found to be so robust that it picked up even the differences in the substrate conditions i.e., a substrate used for coating in an as received form vs a substrate that was grit blasted before spraying showed identifiable differences in the AE signature. An attempt to convert an AE signal to energy and then analyse the spraying process in light of the cumulative energy is an investigation first of its kind in this research, hitherto not seen in the literature. In light of the extensive experimental data gathered from the in-house deposition data, the influence of the release of elastic strain energy based on the particle states and the impact on the substrate has been discussed thoroughly. The interdependency of surface preparation, feed rate and the robotic gun scanning speed has been discussed in detail as well. Through the data presented in this study, we advocate the use of AE analysis to be a vital contributor and a welcome move towards digitalisation of the thermal spray process for in-process monitoring.

Investigation of flexural behaviour of composite rebars for concrete reinforcement with experimental, numerical and machine learning approaches.

Three different types (with glass, basalt and hybrid fibres) of composite rebars manufactured using the pultrusion process were loaded in four-point bending tests. All tests were carried out with acoustic emission sensors to better understand the mechanisms of damage. The data obtained were investigated using standard parameter analysis and also using unsupervised machine learning techniques called K-means. It was found that the best number of clusters is four or five. The numerical model using the finite-element method was calibrated on the basis of the experimental data. Further research will focus on numerical modelling of flexural behaviour of concrete beams reinforced with the presented composite rebars. The presented paper focuses on the characterization of the mechanical properties of composite rebars using a micromechanical approach, as well as analysis of progression damage processes appearing under flexural loading, using different perspectives provided by techniques such as acoustic emission analysis with machine learning-based clustering and numerical simulations. The presented research confirms that the proposed experimental-numerical approach can be applied in order to describe the flexural behaviour of Fibre Reinforcement Polymer (FRP) rods, which is relevant for investigating more complex cases of FRP concrete structures. This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.

Combined effects of solution environment and freeze-thaw cycling on the crack propagation characteristics in sandstone during loading

The failure of ancient rock ruins is affected by freeze-thaw cycles is an important phenomenon in cold region. The degree of freeze-thaw damage be significantly influenced and show an obvious difference during the complex solution environments. However, few studies have been conducted to investigate the combined effects of complex solution environments and freeze-thaw (F-T) cycles to the crack propagation mechanism of loading freeze-thawed sandstones. To study the coupling effects of complex solution environments and freeze-thaw on argillaceous sandstone in ancient ruins, the physical and mechanical properties were investigated through weighing tests, ultrasonic tests, and uniaxial compression tests. The complete failure process of each sample was concurrently monitored using a combination of AE and MS techniques. The crack propagation mechanism at different scales was systematacially investigated through a comparative analysis of microseismic (MS) and acoustic emission (AE) signal characteristics. Additionally, the orthogonal test was designed to effectively analyse the sensitivity of the primary influencing factors to freeze-thawed damage. The findings indicate that:(1) NaCl concentration influences the frost heave force and salt crystallization pressure. While pH levels impact the integrity of the rock structure, leading to significant changes in volume expansion and frost heave force. These aspects are regarded as the main causes of sandstone softening. (2) Compared to the NaCl concentration, varying pH have a more pronounced effect on the freeze-thawed damage. (3) The micro-cracks propagation during loading process is classified into three stages: initial compaction, incubation, and rapid propagation. The macro-cracks propagation is divided into two stages: uniform propagation and rapid propagation. With the increase of NaCl concentration and acidity of solution, the relative duration of incubation in micro-cracks propagation decreased, while the relative duration of uniform propagation in macro-cracks increased. When NaCl concentration and acidity surpass a specific threshold, both the micro-cracks and macro-cracks rapidly propagate from the beginning of the loading process.

A Review of Approaches for Mitigating Effects from Variable Operational Environments on Piezoelectric Transducers for Long-Term Structural Health Monitoring.

Extending the service life of ageing infrastructure, transportation structures, and processing and manufacturing plants in an era of limited resources has spurred extensive research and development in structural health monitoring systems and their integration. Even though piezoelectric transducers are not the only sensor technology for SHM, they are widely used for data acquisition from, e.g., wave-based or vibrational non-destructive test methods such as ultrasonic guided waves, acoustic emission, electromechanical impedance, vibration monitoring or modal analysis, but also provide electric power via local energy harvesting for equipment operation. Operational environments include mechanical loads, e.g., stress induced deformations and vibrations, but also stochastic events, such as impact of foreign objects, temperature and humidity changes (e.g., daily and seasonal or process-dependent), and electromagnetic interference. All operator actions, correct or erroneous, as well as unintentional interference by unauthorized people, vandalism, or even cyber-attacks, may affect the performance of the transducers. In nuclear power plants, as well as in aerospace, structures and health monitoring systems are exposed to high-energy electromagnetic or particle radiation or (micro-)meteorite impact. Even if environmental effects are not detrimental for the transducers, they may induce large amounts of non-relevant signals, i.e., coming from sources not related to changes in structural integrity. Selected issues discussed comprise the durability of piezoelectric transducers, and of their coupling and mounting, but also detection and elimination of non-relevant signals and signal de-noising. For long-term service, developing concepts for maintenance and repair, or designing robust or redundant SHM systems, are of importance for the reliable long-term operation of transducers for structural health monitoring.

Wooden beam damage evaluation under bending loading based on the integration of acoustic emission and principal component analysis

This paper proposes a comprehensive evaluation index based on the combination of acoustic emission (AE) technology and principal component analysis (PCA) to address the issue of low accuracy of any single AE parameter in identifying damage to wooden beams caused by accumulative damage. Four-point bending tests were conducted on wooden beams to monitor the process of performance degradation and evaluate damage progress. The results indicate that the proposed comprehensive evaluation index can divide the damage evolution process of wooden beams into four stages: initial compaction, elastic deformation, crack propagation, and instability fracture. These stages are consistent with the mechanical properties of wooden beams. The time of crack initiation can also be determined according to the comprehensive evaluation index value. The proposed wooden beam damage detection method based on the AE technique provides a reference for further research on the damage evolution mechanism of wooden structures and in situ monitoring methods.

Cross-grain fracture characterization in softwood using artificial neural network analysis of acoustic emissions

Cross-grain fracture characterization in softwood using artificial neural network analysis of acoustic emissions

Experimental Study of the Mechanical and Acoustic Emission Characteristics of Sandstone by Using High-Temperature Water-Cooling Cycles

In order to study the physical and mechanical properties of sandstone under high-temperature water-cooling cycling conditions, an RMT-150B electrohydraulic servo rock testing system and a DS-5 acoustic emission detection and analysis system were used to conduct uniaxial compression acoustic emission tests on sandstone after high-temperature water-cooling cycles. The deformation, strength, and acoustic emission characteristics of sandstone were analyzed under different temperatures and cycle times. The results show that the high-temperature water-cooling effect caused changes in the physical properties of sandstone. The volumetric expansion rate of the rock samples first decreased, then increased in temperature, and the strength first increased, then decreased, whereas the number of cycles had less of an impact on the physical properties. At 200 °C, with increased cycle number, the elastic modulus increased by 20.1%, and the compressive strength increased from 63.9 MPa to 71.46 MPa. At 300–600 °C, the elastic modulus and compressive strength of sandstone gradually decreased with increases in the temperature and cycle number, with reductions of 6.04%, 7.24%, 28.7%, 35.57%, 17.6%, 18.2%, 20.4%, and 60.5%, respectively. With increased temperature and cycle times, the acoustic emission ringing counts increased, ringing counts and cumulative energy appeared earlier, the rock samples entered elastic deformation earlier, the yield stage length increased, and the samples showed a tendency to transition from brittle to ductile damage.

Acoustic Emission Analysis (AEA) in unilateral leg amputees as a future quality tool in orthopaedic technology to evaluate the adjusted prosthesis in relation to gonarthritis

Abstract In orthopaedic technology unilateral leg amputees are provided with prosthesis which are attached through a shaft to the remaining part of the leg. The prosthesis legs are built according to manufacturer’s specifications and get adjusted to the individual needs through motion analysis. If the prosthesis is not adjusted correctly to the individual needs of the user, the chance for development of arthritis in the remaining knee joint is greatly increased. The goal of this paper is to develop a procedure based on AEA to detect signs of arthritis in the remaining knee joint early and the base of a procedure for a future assessment of the quality of the care. The measurement system consists of the AEA - measurement device, a force plate to measure ground reaction forces, two strain gauges which are attached to handles on a test rig and two video cameras which record the movement from frontal and sagittal view. The amputee performs a standard movement in the test rig which consists of three knee bends in ten seconds while wearing the prosthesis legs. The test rig is provided so the amputee can support themselves using arms and hands as prosthesis’ support during the extension phase of the knee bend. The posture and load of the knee joint during the movement is analyzed with the video and force data. The ground reaction forces show the load distribution between the remaining leg and the prosthesis and its support during the movement. The hand forces give clues how well the amputee can balance and which arm is favored under load. By combining kinematic data and AEA the state of the load transfer zones can be evaluated. Thus, it’s possible to examine the remaining knee joint for defects and evaluate the quality of the prosthesis adjustment.